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I really like that it feels like a dynamically typed language but with the security of type inference. That's really cool


That's exactly the feel I've been going for. Instead of "gradual typing", I wondered if there was a way to make everything statically typed but still read from a file. I settled on a combination of type providers (F#) and compile-time function evaluation (D).


Grafana. It's free and open source. However, it's limited to a 5 seconds refresh rate and doesn't stream the data in - only polls data


We heavily use Grafana - It's not limited to 5 seconds that's just the default they ship it with, edit the template from the UI and it does 1 second without any issues.


I cannot fault your enthusiam but I can fault your method :)

Read Tsay's Financial Time Series Analysis for a better idea how to forecast financial data.

The biggest problem you will face is stationarity: the statistical properties of the data is not constant over time. For example, the mean and std dev is not constant over time. Using returns instead of raw prices helps to make better financial forecasts.

Two methods to explore:

1. You are better off predicting stock prices by predicting future returns and then forecasting is the current price plus predicted future return.

2. You could use your neural model to predict absolute size of returns using realized volatility.


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